Eric Medvet
Impact in
- Software top 2%
- Software Testing and Debugging Techniques
- Signal Processing top 1%
- Advanced Malware Detection Techniques
Papers in
-
- Evolutionary Algorithms and Applications 47
- Metaheuristic Optimization Algorithms Research 26
- Reinforcement Learning in Robotics 21
- Natural Language Processing Techniques 14
- Co-authors
- Alberto Bartoli (87 shared papers)Andrea De Lorenzo (49 shared papers)Francesco Mercaldo (10 shared papers)Corrado Aaron Visaggio (6 shared papers)Gerardo Canfora (4 shared papers)Christopher Kruegel (1 shared paper)Engin Kirda (1 shared paper)Felice Andrea Pellegrino (14 shared papers)
In The Last Decade
Eric Medvet
154 papers receiving 1.9k citations
Peers
Comparison fields: 5 of 109
- Software 264
- Signal Processing 655
- Artificial Intelligence 999
- Information Systems 622
- Computer Networks and Communications 586
Countries citing papers authored by Eric Medvet
This map shows the geographic impact of Eric Medvet's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Eric Medvet with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric Medvet more than expected).
Fields of papers citing papers by Eric Medvet
This network shows the impact of papers produced by Eric Medvet. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Eric Medvet. The network helps show where Eric Medvet may publish in the future.
Co-authors
The 25 scholars most cited alongside Eric Medvet, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 164 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2008 | 133 | |
| 2 | 2015 | 117 | |
| 3 | 2021 | 106 | |
| 4 | 2015 | 98 | |
| 5 | 2016 | 73 | |
| 6 | 2014 | 47 | |
| 7 | 2014 | 45 | |
| 8 | 2019 | 43 | |
| 9 | 2015 | 42 | |
| 10 | 2016 | 39 | |
| 11 | 2012 | 36 | |
| 12 | 2011 | 35 | |
| 13 | 2018 | 35 | |
| 14 | 2021 | 33 | |
| 15 | 2018 | 31 | |
| 16 | 2018 | 31 | |
| 17 | 2016 | 29 | |
| 18 | 2020 | 28 | |
| 19 | 2017 | 26 | |
| 20 | 2010 | 26 |
About Eric Medvet
Eric Medvet is a scholar working on Artificial Intelligence, Information Systems, Computer Networks and Communications, Signal Processing and Mechanical Engineering, having authored 164 papers that have together received 2.0k indexed citations. Recurring topics across this work include Evolutionary Algorithms and Applications (47 papers), Metaheuristic Optimization Algorithms Research (26 papers), Network Security and Intrusion Detection (23 papers), Modular Robots and Swarm Intelligence (22 papers), Advanced Malware Detection Techniques (22 papers), Reinforcement Learning in Robotics (21 papers), Micro and Nano Robotics (15 papers) and Natural Language Processing Techniques (14 papers). The work is most often cited by research in Software (264 citations), Signal Processing (655 citations), Artificial Intelligence (999 citations), Information Systems (622 citations) and Computer Networks and Communications (586 citations). Eric Medvet has collaborated with scholars based in Italy, Norway and Portugal. Frequent co-authors include Alberto Bartoli, Andrea De Lorenzo, Francesco Mercaldo, Corrado Aaron Visaggio, Gerardo Canfora, Christopher Kruegel, Engin Kirda, Felice Andrea Pellegrino, Gianfranco Fenu and Fabio Martinelli. Their work appears in journals such as Genetic Programming and Evolvable Machines, Lecture notes in computer science, IEEE Access, IEEE Transactions on Cybernetics and Applied Soft Computing.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.